AbstractThe joint use of multiresolution sensors from different satellites offers many opportunities to describe vegetation and its dynamics. This paper introduces the concept of a virtual constellation (defined as an ensemble of all Earth Observation satellites in orbit that satisfy common requirements) for agricultural applications and contributes to providing the necessary inter-sensor calibration methodology for spectral reflectances and NDVI. For this purpose, we performed an observational study, comparing reflectances and the Normalized Difference Vegetation Index (NDVI), from near-synchronous image pairs of Landsat 7 Enhanced Thematic Mapper Plus (ETM+), as the reference sensor and Landsat 5 Thematic Mapper (TM), IRS 1C/D LISS-III (LISS), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), QuickBird, and NOAA Advanced Very High-resolution Radiometer (AVHRR). Linear relationships were found for the intercalibration of reflectances and NDVI from one sensor to another, for all sensors, provided that some spatial aggregation was performed. The main source of data dispersion in our linear cross-sensor translation equations is the geolocation uncertainty inherent in the process of geometric correction. Consequently, spatial aggregation always needs to be performed if (different or the same) sensors are to be used to derive time-series of biogeophysical parameters over heterogeneous areas. The homogenous zone approach developed here is recommended as an excellent tool for deriving robust new cross-sensor relationships, provided that the selected homogeneous crops cover the full NDVI range. The linear cross-sensor relationships derived from one image pair were shown to be valid for the whole season and for all areas with similar vegetation and climate.